In the United States, there are an estimated 98,000 people killed each year and $17.1 billion dollars lost due to medical errors. One way to prevent these errors is through the use of simulation-based education on human patient simulator systems (“HPS”). HPS systems are perhaps the most commonly used android robots in the United States, and domestically comprise a $70 million dollar industry. Simulated patients provide safe experiences for clinical trainees, where they can practice communication, assessment, and intervention skills, without fear of harming a real patient. Although this technology is in widespread use today, commercial patient simulators lack sufficient realism. Despite the vital importance of non-verbal expressivity to providing cues to clinicians for how to assess and treat patients, currently available commercial HPS systems include static faces and mouth positions, and generally immobile, non-animated body portions, with no capability to convey facial expressions, gaze, and realistic mouth movements, etc. In particular, these simulators cannot convey visual signals of pain to medical trainees, even though perceiving a patient's nonverbal pain cues is an exceptionally important factor in how clinicians make decisions. As a result, existing systems may be preventing students from picking up on patients' pain signals, possibly inculcating poor safety habits due to a lack of realism in the simulation.